Aesthetic quality classification via subject region extraction

Aesthetic quality classification of photos gains growing interest in recent years. In this paper, we propose an aesthetic quality classification method via subject region extraction. We extract the subject region by a combination of clear region detection and saliency detection. Once the subject reg...

Full description

Saved in:
Bibliographic Details
Published inProceedings - International Conference on Image Processing pp. 536 - 540
Main Authors Jonghee Kim, Changick Kim
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2014
Subjects
Aesthetic quality classification
Computer vision
Face
Feature extraction
Histograms
Image color analysis
Machine learning
Random forests
Subject region extraction
Vectors
Visualization
Online AccessGet full text

Cover

More Information
Summary:Aesthetic quality classification of photos gains growing interest in recent years. In this paper, we propose an aesthetic quality classification method via subject region extraction. We extract the subject region by a combination of clear region detection and saliency detection. Once the subject regions are extracted, we extract regional features to measure contrast between the subject and background regions since people usually emphasize objects by focusing them. Global features are used to describe comprehensive properties of the image. Experimental results show that our classification performance outperforms the state-of-the-art aesthetic quality classification methods even if we do not use prior knowledge of a visual content.
ISSN:1522-4880
DOI:10.1109/ICIP.2014.7025107